'''simple docstring'''




import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

__UpperCAmelCase					=imread(R"digital_image_processing/image_data/lena_small.jpg")
__UpperCAmelCase					=cvtColor(img, COLOR_BGR2GRAY)






def __lowerCAmelCase					(				)      ->       Optional[int]:
    __lowerCamelCase            =    cn.convert_to_negative(UpperCamelCase__							)
    # assert negative_img array for at least one True
    assert negative_img.any()






def __lowerCAmelCase					(				)      ->       Any:
    with Image.open('''digital_image_processing/image_data/lena_small.jpg'''							) as img:
        # Work around assertion for response
        assert str(cc.change_contrast(UpperCamelCase__							,    1_10							)							).startswith(
            '''<PIL.Image.Image image mode=RGB size=100x100 at'''							)






def __lowerCAmelCase					(				)      ->       Optional[int]:
    __lowerCamelCase            =    canny.gen_gaussian_kernel(9							,    sigma=1.4							)
    # Assert ambiguous array
    assert resp.all()






def __lowerCAmelCase					(				)      ->       int:
    __lowerCamelCase            =    imread('''digital_image_processing/image_data/lena_small.jpg'''							,    0							)
    # assert ambiguous array for all == True
    assert canny_img.all()
    __lowerCamelCase            =    canny.canny(UpperCamelCase__							)
    # assert canny array for at least one True
    assert canny_array.any()






def __lowerCAmelCase					(				)      ->       Union[str, Any]:
    assert gg.gaussian_filter(UpperCamelCase__							,    5							,    sigma=0.9							).all()






def __lowerCAmelCase					(				)      ->       Dict:
    # laplace diagonals
    __lowerCamelCase            =    array([[0.2_5, 0.5, 0.2_5], [0.5, -3, 0.5], [0.2_5, 0.5, 0.2_5]]							)
    __lowerCamelCase            =    conv.img_convolve(UpperCamelCase__							,    UpperCamelCase__							).astype(UpperCamelCase__							)
    assert res.any()






def __lowerCAmelCase					(				)      ->       Optional[Any]:
    assert med.median_filter(UpperCamelCase__							,    3							).any()






def __lowerCAmelCase					(				)      ->       Optional[int]:
    __lowerCamelCase      ,    __lowerCamelCase            =    sob.sobel_filter(UpperCamelCase__							)
    assert grad.any() and theta.any()






def __lowerCAmelCase					(				)      ->       Any:
    __lowerCamelCase            =    sp.make_sepia(UpperCamelCase__							,    20							)
    assert sepia.all()






def __lowerCAmelCase					(				UpperCamelCase__ = "digital_image_processing/image_data/lena_small.jpg"							)      ->       Tuple:
    __lowerCamelCase            =    bs.Burkes(imread(UpperCamelCase__							,    1							)							,    1_20							)
    burkes.process()
    assert burkes.output_img.any()






def __lowerCAmelCase					(				UpperCamelCase__ = "digital_image_processing/image_data/lena_small.jpg"							,    )      ->       List[Any]:
    __lowerCamelCase            =    rs.NearestNeighbour(imread(UpperCamelCase__							,    1							)							,    4_00							,    2_00							)
    nn.process()
    assert nn.output.any()






def __lowerCAmelCase					(				)      ->       int:
    __lowerCamelCase            =    '''digital_image_processing/image_data/lena.jpg'''

    # Reading the image and converting it to grayscale.
    __lowerCamelCase            =    imread(UpperCamelCase__							,    0							)

    # Test for get_neighbors_pixel function() return not None
    __lowerCamelCase            =    0
    __lowerCamelCase            =    0
    __lowerCamelCase            =    image[x_coordinate][y_coordinate]

    __lowerCamelCase            =    lbp.get_neighbors_pixel(
        UpperCamelCase__							,    UpperCamelCase__							,    UpperCamelCase__							,    UpperCamelCase__							)

    assert neighbors_pixels is not None

    # Test for local_binary_pattern function()
    # Create a numpy array as the same height and width of read image
    __lowerCamelCase            =    np.zeros((image.shape[0], image.shape[1])							)

    # Iterating through the image and calculating the local binary pattern value
    # for each pixel.
    for i in range(0							,    image.shape[0]							):
        for j in range(0							,    image.shape[1]							):
            __lowerCamelCase            =    lbp.local_binary_value(UpperCamelCase__							,    UpperCamelCase__							,    UpperCamelCase__							)

    assert lbp_image.any()

'''simple docstring'''




def __lowerCAmelCase					(				UpperCamelCase__							,    UpperCamelCase__							)      ->       float:
    if digit_amount > 0:
        return round(number - int(UpperCamelCase__							)							,    UpperCamelCase__							)
    return number - int(UpperCamelCase__							)


if __name__ == "__main__":
  print(decimal_isolate(1.53, 0))
  print(decimal_isolate(35.345, 1))
  print(decimal_isolate(35.345, 2))
  print(decimal_isolate(35.345, 3))
  print(decimal_isolate(-14.789, 3))
  print(decimal_isolate(0, 2))
  print(decimal_isolate(-14.123, 1))
  print(decimal_isolate(-14.123, 2))
  print(decimal_isolate(-14.123, 3))
